Statistical learning is a particular form of procedural memory which involves finding the underling pattern in a sequence of stimuli and applying that knowledge to novel stimuli. This project uses a new paradigm for auditory and visual statistical learning in which the underlying pattern in a sequence of tones or images is strictly controlled according to a set of probabilistic rules. We will explore the role of sleep in the consolidation of the knowledge of the underlying pattern in several experiments, combining behavioural measures, sleep measures (polysomnography) and functional neuroimaging (fMRI), in order to fully understand sleep-dependent changes in the brain after implicit acquisition of abstract statistical knowledge and the cross-modal application of this knowledge. This project has been funded by the BBSRC (grant to PL).

One way of organising knowledge of our environment is by the creation and application of mental schemata. A schema is pre-existing mental structure, acquired on the basis of experience, which is triggered by a situation context (such as walking into a restaurant) and which, once triggered, creates a set of expectations as to what else should be present or what should happen next (such as the presence of menus, or being greeted by a waiter). This project looks at the musical schema of tonality, which is acquired purely by growing up in a Western musical culture without needing any explicit training. It asks three fundamental questions: (i) Does the presence of a tonal schema aid memory for schema-conformant items? (ii) Do you need to sleep before having your memory tested in order to benefit from the schema? (iii) Is there brain reorganisation associated with the improved performance that occurs during sleep? We are using a memory test for tonal and atonal melodies, overnight sleep monitoring, and fMRI brain monitoring in order to answer these questions. This project has been funded by the BBSRC (grant to PL).

Insomnia affects a large number of people in the UK each year, leading to a decrease in both the ability to function and quality of life. It also costs a huge amount of money each year (sleep deprivation is estimated to cost £40 billion a year in the UK alone, and insomnia is the leading cause of this). Pharmaceutical interventions are helpful only in a minority of cases, and come with a variety of undesirable side effects. For a long time people have listened to music or the radio at bed time, which many people say helps them sleep. In this project we are investigating the potential benefits of music at bedtime in a variety of ways. The first major part of this is our survey on the use of music to help with sleep, in order to understand what people are currently doing. We are now also undertaking the next part of this project which is home-based intervention study in which we ask participants to listen to a CD we have given them each night before bed for two weeks, during which time we also monitor their sleep patterns with actigraphy as well as record subject sleep quality. We are ultimately interested in finding out what types of music are particularly beneficial for sleep, and applying some scientific rigour in obtaining the evidence. This project has been funded by the EPS (grant to SD).

Over-the-counter (OTC) medicines are a popular alternative to pharmaceutical interventions when faced with problems of insomnia, but most OTC remedies have little or no scientific evidence behind them. Anecdotal reports of fragrance from essential oils such as lavender suggest that they may be beneficial for sleep, so in this project we aim to test this hypothesis and get some hard evidence to support or refute it. We have teamed up with Grantham-based business Microcapture (PET Ltd), who utilise a highly specialised micro-encapsulation technology to coat objects with a fragrance which is then released over time by contact pressure, and preserved until then. This is ideal for overnight use, so our research aims to make use of this by asking participants to use a fragrance-covered pillowcase for a period of two weeks, during which we will monitor their sleep patterns and quality objectively (through actigraphy) and subjectively (through questionnaires). We will compare different fragrances to see which may lead to an improvement in sleep over this period of time. This project has been funded by Innovation UK grant to SF/SD).

We know that rapid eye movement (REM) sleep, which you get more of in the second half of the night, is associated with our most vivid dreams. We also know that areas of the brain involved in emotional arousal – including the amygdala – are strongly active during REM sleep, and a growing body of research suggests that REM sleep is involved in consolidating emotional memories. However, we do not always want to retain our emotional memories; ideally we would like to forget, or at least tone down, our negative emotional memories while strengthening our positive ones. Recent evidence suggests that this may be possible using appropriate types of transcranial direct current stimulation (tDCS). This project investigates this intriguing hypothesis, by looking at emotional memory consolidation when applying tDCS stimulation in REM sleep at an appropriate frequency and comparing it with other possibilities (such as application of lower frequency tDCS during deep slow wave sleep, or no stimulation at all). This is an ambitious and highly experimental piece of work that is an MSc thesis for the lead researcher.

Given the involvement of REM sleep in emotional memory consolidation (see the project listed above), and the potential impact of excessive negative memory consolidation on low mood, it may be the case that having increased REM sleep or REM density will predispose someone towards depression, especially if it is combined with a negative bias coming from strong amygdala activation. This is the proposal of our recent Affect Tagging and Consolidation (ATaC) model developed by the researchers. This involves several studies examining the relationship between REM sleep parameters (such as duration and density) and emotional memory consolidation in participants with mild to moderate depressive symptoms and healthy controls. We are also looking at the genetic basis of this, examining the serotonin transporter gene (5-HTT) and brain-derived neurotrophic factor gene (BDNF Val66Met), to better understand the complex relationship between different genotypes, REM sleep parameters, emotional memory consolidation and mood. This is again highly experimental and ambitious work which is being carried out as a PhD project by the lead researcher. This project has been funded by a College of Social Science PhD Studentship (University of Lincoln).

Computational neuroscience involves modelling parts of the brain at a level of biophysical realism that goes beyond artificial neural networks or cognitive neuroscience models, with a view to understanding the dynamic behaviour of the brain. This can be done using different approaches and at different levels of detail, and in this project looking at how sleep EEG is generated in the brain, we adopt two complementary approaches. One paradigm is neural mass modelling – using a single unit representing a mass of tissue of a certain size and with a single set of parameters describing its behaviour, and using this approach we have built on previous work by implementing a thalamic module and a cortical module and connecting the two. Our simulation results show amongst other things the important role played by thalamic inhibitory interneurons. Alongside this, we are working at the individual neuron level, using specialised hardware in the form of a SpiNNaker board (for simulating networks of spiking neurons) and a hardware retina model (developed by one of the researchers), and amongst other things looking at EEG during drowsy driving and seeing if it is possible to simulate that with a view to developing preventative warnings.